Biodiversity Conservation

We work with the objective of contributing to the biodiversity conservation in environmental, social and economic aspects.

Climate change

We support decision makers in the climate agenda focused on ecosystem conservation and restoration projects and biodiversity.

Ecosystem restoration

The approaches developed by IIS aim to assist the planning and implementation of vegetation recovery projects, exploring synergies and trade-offs between biodiversity conservation, climate change mitigation and costs, under a variety of scenarios.

Sustainable development

We seek to promote the transition to sustainability, contributing to the balance between socioeconomic development, biodiversity conservation and rational use of natural resources.

Sustainable Land Use

We promote the transition from the traditional agricultural practices to a more sustainable land management, helping to mitigate climate change and guaranteeing the future of the next generations.

Economic Analysis

We seek to strengthen and defend the basic principles of balance between the economy and the environment, favoring research, planning and management in public and private fields, linked to the relationship between ecological, social and economic systems, in order to improve social well-being.

Policies

We assist in the formulation of policies aimed at sustainability, as well as the implementation of practical actions, working in partnership with public sector bodies and other organizations.

Spatial intelligence

Through landscape modeling and monitoring, we identify the patterns and trends of social and ecological systems, supporting decision makers through quantitative statistics and mapped scenarios.

Publications > Article

Share

A new approach to map landscape variation in forest restoration success in tropical and temperate forest biomes

A high variation level of the recovery´s biodiversity of a landscape during forest restoration, presents obstacles to ensure large‐scale, cost‐effective and long‐lasting ecological restoration. There is an urgent need to predict landscape variation in forest restoration success at a global scale. We conducted a meta‐analysis comprising 135 study landscapes to predict and map landscape variation in forest restoration success in tropical and temperate forest biomes. Our analysis was based on the amount of forest cover within a landscape, where we identified the most plausible model to predict and map landscape variation in forest restoration success.

Related Themes

Related collaborators (1)

Bernardo Baeta Neves Strassburg

Co-founder